Mayfield Maths Coursework

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Introduction

Maths

Statistics Coursework Yr10

Correlation between: The more hours spent in the gym the more amount of weight you will loose.

Explanation on correlation

This is a scatter graph on the following correlation and is a positive correlation between the more hours you will spend in the gym the more weight you will loose. This shows that if people stay healthy then they would weight less. I will now work out the mean, mode and median of certain numbers to prove the correlation and prove that the correlation is correct. I will also be having a stem and leaf diagram and a inter quartile range which will also prove my correlation.

Firstly to prove that my correlation is positive and is correct I will create a stem and leaf diagram which is a diagram that shows data in a systematic way and the mode median and mean can be found easily from this. Once the stem and leaf diagram is created I can then find the average, mean, mode and median of the correlation.

Stem and leaf Diagram

Gym hours

Weight

2468

0

024

1

2

3

4

5

04567

6

02345

7

02478

8

4689

9

048

This is the stem and leaf diagram for the correlation between gym hours and weight, finding the mean, mode and median should be much easier now.

Average of Gym hours (D2:D17) =-3.375

Average of weight (E2:E17) =63.25

That is one way of finding an average to support the correlation between gym hours and weight. Here is another way:

Mode number of gym hours: 14hrs

Mode number of weight: 57

This average is saying spending 14hrs at the gym will make you loose 57 pounds of weight which is supporting my correlation.

This is because the stem and leaf diagram has made it easier to fine the mean mode and median. I have also found the interquartal range I have now proven that the correlation between weight and sick days is correct.

Correlation between: The more amounts of sick days the more amount of salary lost

Explanation on correlation

This is a following scatter graph on the following correlation and is a negative correlation between the more amount of sick days you will have the more amount of salary lost. The correlation is showing that if people have so many sick days then they will start to lose their salary. I am now going to show how I can prove that the following negative correlation is right or wrong by taking the mean median and mode and the average of the correlation. . I will be also having a stem and leaf diagram and an interquaritle range which will also prove my correlation.

Firstly to prove that my correlation is negative and correct I will create a stem and leaf diagram which is a diagram that shows data in a systematic way and the mode median and mean can be found easily from this. Once the stem and leaf diagram is created I can then find the average, mean, mode and median of the correlation.

Stem and leaf Diagram

Sick days

Salary

2345678

0

02

1

785928

2

051225344589965

3

4

3

5

6

7

8

9

This is the stem and leaf diagram for the correlation between sick days’s and weight, to find the mode, mean and median now should be easier

This is the stem and leaf diagram for the correlation between sick day and weight, to find the mode, mean and median now should be easier

Average of age :( B2:B51) =36.98

Average of salary: (C2:C51) =28683.67

That is one way of finding an average to support the correlation between age and salary. Here is another way:

Mode number of age: 18

Mode number of salary:21000

This average is saying people that aged 18 only earn 21,000 which shows that my correlation is correct.

Mean of age: 17, 18, 19, 20=19

Mean of salary: 17, 000, 18, 000, 18, 500, 19,000=181500

Here it is also saying that people who are aged 19 earn 181500 this shows that my correlation is wrong by using the mean I cannot prove my correlation.

Median of age: (B2:B17) = 21

Median of salary: (C2:C17) =21000

Interquaritle range:

Lower quartile range on age:

¼(N+1) =

¼(11+1) =third term=19

Upper quartile range on age:

¾(N+1) =

¾(11+1) =nine term=32

Lower quartile range on salary:

¼(N+1) =

¼(11+1) =third term=2100

Upper quartile range on salary:

¾(N+1) =

¾(11+1) =nine term=2750

We know the average of the correlation and we can now prove that correlation between age and salary that people who are older do get more salary it is now proven that my correlation is correct.

This is because the stem and leaf diagram has made it easier to fine the mean mode and median. I have also found the interquartal range I have now proven that the correlation between gym hours and sick days is correct.

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